Field of Invention
The present invention relates to a metrology sampling method with a sampling rate decision scheme. More particularly, the present invention relates to a metrology sampling method for reducing and automatically adjusting a workpiece sampling rate.
Description of Related Art
Nowadays, most of the semiconductor and TFT-LCD plants adopt sampling test methods to monitor the quality of each product or workpiece (i.e. “wafer” in IC foundries or “glass” in TFT-LCD factories) processed by process tools. In general, after each N (for example, 25) workpieces are processed by the process tool, a manufacturing system designates the Nth workpiece in the each N workpieces as a workpiece expected (scheduled) to be measured, i.e. the sampling rate is fixed as 1/N. The workpiece expected to be measured then will be sent to a metrology tool for measurement, thereby inspecting the production quality of the process tool. This conventional sampling method is based on the presupposition that no abnormal circumstances will abruptly occur in the production processes, and thus the measurement result of the sampled product or workpiece can be used to determine the quality of the workpieces in the same lot with the sampled workpiece. Because the measurement time and tool required by the real workpiece metrology result in the increase of cycle time and production cost. Therefore, reducing the sampling rate to as low as possible is an important task for manufactures for reducing cycle time and production cost. Besides, the value of the conventional workpiece sampling rate 1/N is selected merely in accordance with an experience value of the manufacturing system without other technical bases, and thus cannot be effectively adjusted.
On the other hand, virtual metrology (VM) can be used to lower the frequency of actual measurement on workpiece to reduce the sampling rate. However, if a production variation occurs on the workpiece which is unplanned for measurement, no real metrology is available during this period for updating the VM models, thus resulting in poor VM prediction accuracy. Therefore, how to sample and obtain an appropriate workpiece in time affects the prediction accuracy of VM models.
Hence, there is a need to provide a metrology sampling method for overcoming the aforementioned shortcomings of the conventional skill.